Faculty profile

Jennifer Howcroft

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is a Lecturer in the Department of Systems Design Engineering at the University of Waterloo.University of Waterloo

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Research

Read how they describe their research on their University of Waterloo profile.

Latest papers

Validation of the Candrive Older Driver Risk Stratification Tool for Assessing Medical Fitness-to-Drive in Older Australian Drivers
The journals of gerontology. Series A, Biological sciences and medical sciences · 2025
Fall risk assessment in the wild: A critical examination of wearable sensor use in free-living conditions.
Gait & posture · 2021
Dual-Task Elderly Gait of Prospective Fallers and Non-Fallers: A Wearable-Sensor Based Analysis.
Sensors (Basel, Switzerland) · 2018 · first author

All 11 publications

11 publications.

Validation of the Candrive Older Driver Risk Stratification Tool for Assessing Medical Fitness-to-Drive in Older Australian Drivers

Charlton JL, Koppel S, Stephens A, Bedard M, Howcroft J, Darzins P, Di Stefano M, Gagnon S, Gelinas I, Man-Son-Hing M

The journals of gerontology. Series A, Biological sciences and medical sciences2025

DOI: 10.1093/gerona/glaf071

Fall risk assessment in the wild: A critical examination of wearable sensor use in free-living conditions.

Nouredanesh M, Godfrey A, Howcroft J, Lemaire ED, Tung J

Gait & posture2021

DOI: 10.1016/j.gaitpost.2020.04.010 PMID: 33601319

Dual-Task Elderly Gait of Prospective Fallers and Non-Fallers: A Wearable-Sensor Based Analysis.

Howcroft J, Lemaire ED, Kofman J, McIlroy WE

Sensors (Basel, Switzerland)2018First author

DOI: 10.3390/s18041275 PMID: 29690496

Faller Classification in Older Adults Using Wearable Sensors Based on Turn and Straight-Walking Accelerometer-Based Features.

Drover D, Howcroft J, Kofman J, Lemaire ED

Sensors (Basel, Switzerland)2017

DOI: 10.3390/s17061321 PMID: 28590432

Feature selection for elderly faller classification based on wearable sensors.

Howcroft J, Kofman J, Lemaire ED

Journal of neuroengineering and rehabilitation2017First author

DOI: 10.1186/s12984-017-0255-9 PMID: 28558724

Elderly fall risk prediction using static posturography.

Howcroft J, Lemaire ED, Kofman J, McIlroy WE

PloS one2017First author

DOI: 10.1371/journal.pone.0172398 PMID: 28222191

Analysis of dual-task elderly gait in fallers and non-fallers using wearable sensors.

Howcroft J, Kofman J, Lemaire ED, McIlroy WE

Journal of biomechanics2016First author

DOI: 10.1016/j.jbiomech.2016.01.015 PMID: 26994786

Wearable-Sensor-Based Classification Models of Faller Status in Older Adults.

Howcroft J, Lemaire ED, Kofman J

PloS one2016First author

DOI: 10.1371/journal.pone.0153240 PMID: 27054878

Understanding responses to gait instability from plantar pressure measurement and the relationship to balance and mobility in lower-limb amputees.

Howcroft J, Lemaire ED, Kofman J, Kendell C

Clinical biomechanics (Bristol, Avon)2016First author

DOI: 10.1016/j.clinbiomech.2015.11.004 PMID: 26651474

Understanding dynamic stability from pelvis accelerometer data and the relationship to balance and mobility in transtibial amputees.

Howcroft J, Lemaire ED, Kofman J, Kendell C

Gait & posture2015First author

DOI: 10.1016/j.gaitpost.2015.03.001 PMID: 25804844

Profile data last refreshed on September 27, 2026 from the university directory, publication records and public research funding records.

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Jennifer Howcroft

Research

Latest papers

Validation of the Candrive Older Driver Risk Stratification Tool for Assessing Medical Fitness-to-Drive in Older Australian Drivers

Fall risk assessment in the wild: A critical examination of wearable sensor use in free-living conditions.

Dual-Task Elderly Gait of Prospective Fallers and Non-Fallers: A Wearable-Sensor Based Analysis.

Faller Classification in Older Adults Using Wearable Sensors Based on Turn and Straight-Walking Accelerometer-Based Features.

Feature selection for elderly faller classification based on wearable sensors.

Elderly fall risk prediction using static posturography.

Analysis of dual-task elderly gait in fallers and non-fallers using wearable sensors.

Wearable-Sensor-Based Classification Models of Faller Status in Older Adults.

Understanding responses to gait instability from plantar pressure measurement and the relationship to balance and mobility in lower-limb amputees.

Understanding dynamic stability from pelvis accelerometer data and the relationship to balance and mobility in transtibial amputees.

Frequent collaborators

Jonathan Kofman

Mark Rapoport

Michel Bédard

Shawn Marshall

Gary Naglie

Cynthia Kendell

Brenda Vrkljan

James Tung

Jennifer Howcroft

Research

Latest papers

Validation of the Candrive Older Driver Risk Stratification Tool for Assessing Medical Fitness-to-Drive in Older Australian Drivers

Fall risk assessment in the wild: A critical examination of wearable sensor use in free-living conditions.

Dual-Task Elderly Gait of Prospective Fallers and Non-Fallers: A Wearable-Sensor Based Analysis.

Faller Classification in Older Adults Using Wearable Sensors Based on Turn and Straight-Walking Accelerometer-Based Features.

Feature selection for elderly faller classification based on wearable&#xa0;sensors.

Elderly fall risk prediction using static posturography.

Analysis of dual-task elderly gait in fallers and non-fallers using wearable sensors.

Wearable-Sensor-Based Classification Models of Faller Status in Older Adults.

Understanding responses to gait instability from plantar pressure measurement and the relationship to balance and mobility in lower-limb amputees.

Understanding dynamic stability from pelvis accelerometer data and the relationship to balance and mobility in transtibial amputees.

Frequent collaborators

Jonathan Kofman

Mark Rapoport

Michel Bédard

Shawn Marshall

Gary Naglie

Cynthia Kendell

Brenda Vrkljan

James Tung

Feature selection for elderly faller classification based on wearable sensors.